Unmanned aerial vehicle-assisted energy-efficient data collection scheme for sustainable wireless sensor networks

Recently, wireless sensor networks (WSNs), consisted of battery-powered sensor nodes, are widely adopted by various civilian/military applications for implementing real-time monitoring or long-term surveillance tasks. However, due to limited battery capacity, sensor lifetime is limited, which in turn affects the working time of the whole system. Therefore, solving the problem of improving energy efficiency is the premise for constructing a sustainable/energy-efficient WSN. To address this problem, by taking advantage of the emerging unmanned aerial vehicle (UAV) techniques, we propose a novel UAV-assisted data collection scheme for improving the energy efficiency of the deployed WSN. To meet the performance requirements of systems with different scales, our algorithm has two working modes: single- and multiple-UAV scenarios. For the small-scale system, a single UAV considered data-collector is adopted to access and collect data from the deployed nodes. For the large-scale system, based on a newly designed clustering method, multiple data collectors are utilized to gathering sensed data from the deployed nodes for conserving their energy and reducing the data forwarding latency. To evaluate our proposed work, intensive simulation experiments are conducted. The results demonstrate that the proposed algorithm achieved better performance than the control group regarding system-wide energy efficiency and average end-to-end delay.

Duke Scholars

Author Peng Sun DKU Faculty